SystemVent
* Consultant Data Engineering (6347)
We tailor your resume to this role and apply for you in seconds.
Apply to * Consultant Data Engineering (6347) at SystemVentJob details
- Work type
- Hybrid
- Posted
- May 11, 2026
- Apply on
- career55.sapsf.eu
About this role
* Consultant Data Engineering (6347)
ID: 6347 - Posted - Country (1) - City (5) - 3-4 Years
Job Summary
We are seeking a skilled and detail-oriented Data Engineer to design, develop, and maintain scalable data pipelines and data infrastructure. The ideal candidate will work closely with Data Analysts, Data Scientists, and business stakeholders to ensure reliable data availability, quality, and accessibility across the organization.
Responsiblity:
- Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
- Develop and optimize data models, data warehouses, and lakehouse architectures.
- Integrate data from multiple sources including APIs, databases, cloud platforms, and third-party systems.
- Ensure data quality, consistency, governance, and security standards are maintained.
- Monitor and troubleshoot data workflows, pipeline failures, and performance bottlenecks.
- Collaborate with cross-functional teams including BI, Analytics, Product, and Engineering.
- Automate data processing and deployment workflows using CI/CD practices.
- Optimize SQL queries and database performance for large-scale datasets.
- Support reporting, analytics, and machine learning initiatives by providing reliable datasets.
- Create and maintain technical documentation for data architecture and processes.
Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field.
- Strong experience with SQL and relational databases.
- Hands-on experience with Python, PySpark, or Scala.
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Strong understanding of data warehousing concepts and big data technologies.
- Experience with tools such as Apache Spark, Airflow, Kafka, Databricks, Snowflake, or Hadoop.
- Knowledge of ETL/ELT frameworks and orchestration tools.
- Familiarity with data governance, security, and compliance standards.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management abilities.
Email this job to a friend
The job has been sent to
| Please provide the information below | |
|---|---|
| Job title: | |
| *Your friend’s email address: | |
| Message: |
|
| *Confirm you are not a robot: |
ID: 6347 - Posted - Country (1) - City (5) - 3-4 Years
Job Summary
We are seeking a skilled and detail-oriented Data Engineer to design, develop, and maintain scalable data pipelines and data infrastructure. The ideal candidate will work closely with Data Analysts, Data Scientists, and business stakeholders to ensure reliable data availability, quality, and accessibility across the organization.
Responsiblity:
- Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
- Develop and optimize data models, data warehouses, and lakehouse architectures.
- Integrate data from multiple sources including APIs, databases, cloud platforms, and third-party systems.
- Ensure data quality, consistency, governance, and security standards are maintained.
- Monitor and troubleshoot data workflows, pipeline failures, and performance bottlenecks.
- Collaborate with cross-functional teams including BI, Analytics, Product, and Engineering.
- Automate data processing and deployment workflows using CI/CD practices.
- Optimize SQL queries and database performance for large-scale datasets.
- Support reporting, analytics, and machine learning initiatives by providing reliable datasets.
- Create and maintain technical documentation for data architecture and processes.
Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field.
- Strong experience with SQL and relational databases.
- Hands-on experience with Python, PySpark, or Scala.
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Strong understanding of data warehousing concepts and big data technologies.
- Experience with tools such as Apache Spark, Airflow, Kafka, Databricks, Snowflake, or Hadoop.
- Knowledge of ETL/ELT frameworks and orchestration tools.
- Familiarity with data governance, security, and compliance standards.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management abilities.
Email this job to a friend
The job has been sent to
The job has been sent to
Job Summary
We are seeking a skilled and detail-oriented Data Engineer to design, develop, and maintain scalable data pipelines and data infrastructure. The ideal candidate will work closely with Data Analysts, Data Scientists, and business stakeholders to ensure reliable data availability, quality, and accessibility across the organization.
Responsiblity:
- Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
- Develop and optimize data models, data warehouses, and lakehouse architectures.
- Integrate data from multiple sources including APIs, databases, cloud platforms, and third-party systems.
- Ensure data quality, consistency, governance, and security standards are maintained.
- Monitor and troubleshoot data workflows, pipeline failures, and performance bottlenecks.
- Collaborate with cross-functional teams including BI, Analytics, Product, and Engineering.
- Automate data processing and deployment workflows using CI/CD practices.
- Optimize SQL queries and database performance for large-scale datasets.
- Support reporting, analytics, and machine learning initiatives by providing reliable datasets.
- Create and maintain technical documentation for data architecture and processes.
Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related field.
- Strong experience with SQL and relational databases.
- Hands-on experience with Python, PySpark, or Scala.
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Strong understanding of data warehousing concepts and big data technologies.
- Experience with tools such as Apache Spark, Airflow, Kafka, Databricks, Snowflake, or Hadoop.
- Knowledge of ETL/ELT frameworks and orchestration tools.
- Familiarity with data governance, security, and compliance standards.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management abilities.
Ready to apply to SystemVent?
We tailor your resume to this role and apply for you.